I'm an AI Engineer with nearly 4 years of experience building production systems across startups and large enterprises. I work at the intersection of AI, backend engineering, data, and automation, and I'm most useful when the problem is complex, ambiguous, or still taking shape.

I don't need much handholding. Give me the context, the constraints, and the outcome you're trying to achieve, and I can usually take it from there. I learn unfamiliar systems quickly, ask the right questions early, and work comfortably both independently and within engineering teams.

I've worked on systems involving LLMs, RAG, AI agents, OCR and document intelligence, voice AI, and machine learning, APIs, databases, integrations, and data pipelines. But I don't like defining myself by a fixed stack. Technologies change quickly. Strong fundamentals, clear thinking, and the ability to learn are far more durable.

Production engineering also means thinking beyond whether the code runs. I pay attention to security, data privacy, compliance, auditability, reliability, and architecture, especially when building systems that handle sensitive or business-critical data.

Curiosity drives a lot of my work. I enjoy reading research papers, digging below library abstractions, experimenting with new approaches, and understanding why a system works instead of only learning how to use it.

My long-term goal is simple: expand the surface area of what I can understand and build. I care more about becoming a stronger engineer and creating meaningful value than chasing a particular title or technology.

And if you're working on something technically ambitious, slightly unusual, or genuinely difficult to build, I'd love to hear about it.

I'm also working toward contributing more to open source. It's outside my current comfort zone, which is exactly why I want to go there.